Recommendations from Comments on Online Social Networks

ABSTRACT

In one embodiment, a method includes, by one or more computing devices, receiving, from a client system of a first user of an online social network, a text post inputted by the first user, parsing the text post to identify a query associated with the text post, sending, to the client system, instructions for presenting a confirmation prompt requesting confirmation of the identified query from the first user, receiving, from the client system, a confirmation of the identified query from the first user, generating, in response to receiving the confirmation, a recommendation list responsive to the query, wherein the recommendation list comprises references to one or more objects referenced in one or more prior comments associated with one or more prior posts of the online social network associated with the query, and sending, to the client system, instructions for presenting the recommendation list to the first user.

PRIORITY

This application is a continuation under 35 U.S.C. § 120 of U.S. patentapplication Ser. No. 16/570,983, filed 13 Sep. 2019, which is acontinuation under 35 U.S.C. § 120 of U.S. patent application Ser. No.15/139028, filed 26 Apr. 2016, now U.S. Pat. No. 11,531,678, issuing on20 Dec. 2022, which are incorporated herein by reference.

TECHNICAL FIELD

This disclosure generally relates to social graphs and generatingcontent within a social-networking environment.

BACKGROUND

A social-networking system, which may include a social-networkingwebsite, may enable its users (such as persons or organizations) tointeract with it and with each other through it. The social-networkingsystem may, with input from a user, create and store in thesocial-networking system a user profile associated with the user. Theuser profile may include demographic information, communication-channelinformation, and information on personal interests of the user. Thesocial-networking system may also, with input from a user, create andstore a record of relationships of the user with other users of thesocial-networking system, as well as provide services (e.g. wall posts,photo-sharing, event organization, messaging, games, or advertisements)to facilitate social interaction between or among users.

The social-networking system may send over one or more networks contentor messages related to its services to a mobile or other computingdevice of a user. A user may also install software applications on amobile or other computing device of the user for accessing a userprofile of the user and other data within the social-networking system.The social-networking system may generate a personalized set of contentobjects to display to a user, such as a newsfeed of aggregated storiesof other users connected to the user.

Social-graph analysis views social relationships in terms of networktheory consisting of nodes and edges. Nodes represent the individualactors within the networks, and edges represent the relationshipsbetween the actors. The resulting graph-based structures are often verycomplex. There can be many types of nodes and many types of edges forconnecting nodes. In its simplest form, a social graph is a map of allof the relevant edges between all the nodes being studied.

SUMMARY OF PARTICULAR EMBODIMENTS

In particular embodiments, the social-networking system may receive atext post inputted by a user of an online social network and parse thetext post to identify a query associated with the post. The query may bea request by the user for recommendations about, for example, a place,activity, service, event, etc. For example, a user may post to theonline social network asking others for thing-to-do in a city, e.g.,“I'm going to Barcelona next week, what should I do there?” Thesocial-networking system may then receive one or more comments fromother users responding to the post with particular recommendations, andmay identify objects of the online social network associated with therecommendations. For example, a friend of the user may reply to the postwith a comment that says “You should visit Parc Guell. It's lovely!” Thesocial-networking system may parse this comment and determine that thecommenter is providing a recommendation for the Parc Guell in Barcelona,Spain, which corresponds to a particular profile page of the onlinesocial network. The social-networking system may then generate arecommendation list including references to the identified objects whichthe users can interact with in the online social network. For example,in response to the recommendations provided by the querying user'sfriends, the social-networking system may generate a recommendation listfor “Things to do in Barcelona,” which includes reference to the ParcGuell and other places recommended by the user's friends in the commentsto the post.

The embodiments disclosed above are only examples, and the scope of thisdisclosure is not limited to them. Particular embodiments may includeall, some, or none of the components, elements, features, functions,operations, or steps of the embodiments disclosed above. Embodimentsaccording to the invention are in particular disclosed in the attachedclaims directed to a method, a storage medium, a system and a computerprogram product, wherein any feature mentioned in one claim category,e.g. method, can be claimed in another claim category, e.g. system, aswell. The dependencies or references back in the attached claims arechosen for formal reasons only. However any subject matter resultingfrom a deliberate reference back to any previous claims (in particularmultiple dependencies) can be claimed as well, so that any combinationof claims and the features thereof are disclosed and can be claimedregardless of the dependencies chosen in the attached claims. Thesubject-matter which can be claimed comprises not only the combinationsof features as set out in the attached claims but also any othercombination of features in the claims, wherein each feature mentioned inthe claims can be combined with any other feature or combination ofother features in the claims. Furthermore, any of the embodiments andfeatures described or depicted herein can be claimed in a separate claimand/or in any combination with any embodiment or feature described ordepicted herein or with any of the features of the attached claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example network environment associated with asocial-networking system.

FIG. 2 illustrates an example social graph.

FIGS. 3A and 3B illustrate an example graphical interface for requestingrecommendations in a social-networking system, according to particularembodiments.

FIGS. 4A and 4B illustrate an example graphical interface for requestingrecommendations in a social-networking system, according to particularembodiments.

FIGS. 5A and 5B illustrate an example graphical interface for providingrecommendations in a social-networking system using type-aheadprocesses, according to particular embodiments.

FIGS. 6A and 6B illustrate an example graphical interface for displayinga recommendation list, according to particular embodiments.

FIGS. 7A and 7B illustrate an example graphical interface for displayinga recommendation list and particular comments, according to particularembodiments.

FIG. 8 illustrates an example graphical interface for displaying defaultrecommendations, according to particular embodiments.

FIG. 9 illustrates an example method 900 for generating a list ofrecommendations based on a social network post and associated comments.

FIG. 10 illustrates an example computer system.

DESCRIPTION OF EXAMPLE EMBODIMENTS System Overview

FIG. 1 illustrates an example network environment 100 associated with asocial-networking system. Network environment 100 includes a clientsystem 130, a social-networking system 160, and a third-party system 170connected to each other by a network 110. Although FIG. 1 illustrates aparticular arrangement of a client system 130, a social-networkingsystem 160, a third-party system 170, and a network 110, this disclosurecontemplates any suitable arrangement of a client system 130, asocial-networking system 160, a third-party system 170, and a network110. As an example and not by way of limitation, two or more of a clientsystem 130, a social-networking system 160, and a third-party system 170may be connected to each other directly, bypassing a network 110. Asanother example, two or more of a client system 130, a social-networkingsystem 160, and a third-party system 170 may be physically or logicallyco-located with each other in whole or in part. Moreover, although FIG.1 illustrates a particular number of client systems 130,social-networking systems 160, third-party systems 170, and networks110, this disclosure contemplates any suitable number of client systems130, social-networking systems 160, third-party systems 170, andnetworks 110. As an example and not by way of limitation, networkenvironment 100 may include multiple client systems 130,social-networking systems 160, third-party systems 170, and networks110.

This disclosure contemplates any suitable network 110. As an example andnot by way of limitation, one or more portions of a network 110 mayinclude an ad hoc network, an intranet, an extranet, a virtual privatenetwork (VPN), a local area network (LAN), a wireless LAN (WLAN), a widearea network (WAN), a wireless WAN (WWAN), a metropolitan area network(MAN), a portion of the Internet, a portion of the Public SwitchedTelephone Network (PSTN), a cellular telephone network, or a combinationof two or more of these. A network 110 may include one or more networks110.

Links 150 may connect a client system 130, a social-networking system160, and a third-party system 170 to a communication network 110 or toeach other. This disclosure contemplates any suitable links 150. Inparticular embodiments, one or more links 150 include one or morewireline (such as for example Digital Subscriber Line (DSL) or Data OverCable Service Interface Specification (DOCSIS)), wireless (such as forexample Wi-Fi or Worldwide Interoperability for Microwave Access(WiMAX)), or optical (such as for example Synchronous Optical Network(SONET) or Synchronous Digital Hierarchy (SDH)) links. In particularembodiments, one or more links 150 each include an ad hoc network, anintranet, an extranet, a VPN, a LAN, a WLAN, a WAN, a WWAN, a MAN, aportion of the Internet, a portion of the PSTN, a cellulartechnology-based network, a satellite communications technology-basednetwork, another link 150, or a combination of two or more such links150. Links 150 need not necessarily be the same throughout a networkenvironment 100. One or more first links 150 may differ in one or morerespects from one or more second links 150.

In particular embodiments, a client system 130 may be an electronicdevice including hardware, software, or embedded logic components or acombination of two or more such components and capable of carrying outthe appropriate functionalities implemented or supported by a clientsystem 130. As an example and not by way of limitation, a client system130 may include a computer system such as a desktop computer, notebookor laptop computer, netbook, a tablet computer, e-book reader, GPSdevice, camera, personal digital assistant (PDA), handheld electronicdevice, cellular telephone, smartphone, other suitable electronicdevice, or any suitable combination thereof. This disclosurecontemplates any suitable client systems 130. A client system 130 mayenable a network user at a client system 130 to access a network 110. Aclient system 130 may enable its user to communicate with other users atother client systems 130.

In particular embodiments, a client system 130 may include a web browser132, and may have one or more add-ons, plug-ins, or other extensions. Auser at a client system 130 may enter a Uniform Resource Locator (URL)or other address directing a web browser 132 to a particular server(such as server 162, or a server associated with a third-party system170), and the web browser 132 may generate a Hyper Text TransferProtocol (HTTP) request and communicate the HTTP request to server. Theserver may accept the HTTP request and communicate to a client system130 one or more Hyper Text Markup Language (HTML) files responsive tothe HTTP request. The client system 130 may render a web interface (e.g.a webpage) based on the HTML files from the server for presentation tothe user. This disclosure contemplates any suitable source files. As anexample and not by way of limitation, a web interface may be renderedfrom HTML files, Extensible Hyper Text Markup Language (XHTML) files, orExtensible Markup Language (XML) files, according to particular needs.Such interfaces may also execute scripts, combinations of markuplanguage and scripts, and the like. Herein, reference to a web interfaceencompasses one or more corresponding source files (which a browser mayuse to render the web interface) and vice versa, where appropriate.

In particular embodiments, the social-networking system 160 may be anetwork-addressable computing system that can host an online socialnetwork. The social-networking system 160 may generate, store, receive,and send social-networking data, such as, for example, user-profiledata, concept-profile data, social-graph information, or other suitabledata related to the online social network. The social-networking system160 may be accessed by the other components of network environment 100either directly or via a network 110. As an example and not by way oflimitation, a client system 130 may access the social-networking system160 using a web browser 132, or a native application associated with thesocial-networking system 160 (e.g., a mobile social-networkingapplication, a messaging application, another suitable application, orany combination thereof) either directly or via a network 110. Inparticular embodiments, the social-networking system 160 may include oneor more servers 162. Each server 162 may be a unitary server or adistributed server spanning multiple computers or multiple datacenters.Servers 162 may be of various types, such as, for example and withoutlimitation, web server, news server, mail server, message server,advertising server, file server, application server, exchange server,database server, proxy server, another server suitable for performingfunctions or processes described herein, or any combination thereof. Inparticular embodiments, each server 162 may include hardware, software,or embedded logic components or a combination of two or more suchcomponents for carrying out the appropriate functionalities implementedor supported by server 162. In particular embodiments, thesocial-networking system 160 may include one or more data stores 164.Data stores 164 may be used to store various types of information. Inparticular embodiments, the information stored in data stores 164 may beorganized according to specific data structures. In particularembodiments, each data store 164 may be a relational, columnar,correlation, or other suitable database. Although this disclosuredescribes or illustrates particular types of databases, this disclosurecontemplates any suitable types of databases. Particular embodiments mayprovide interfaces that enable a client system 130, a social-networkingsystem 160, or a third-party system 170 to manage, retrieve, modify,add, or delete, the information stored in data store 164.

In particular embodiments, the social-networking system 160 may storeone or more social graphs in one or more data stores 164. In particularembodiments, a social graph may include multiple nodes—which may includemultiple user nodes (each corresponding to a particular user) ormultiple concept nodes (each corresponding to a particular concept)—andmultiple edges connecting the nodes. The social-networking system 160may provide users of the online social network the ability tocommunicate and interact with other users. In particular embodiments,users may join the online social network via the social-networkingsystem 160 and then add connections (e.g., relationships) to a number ofother users of the social-networking system 160 whom they want to beconnected to. Herein, the term “friend” may refer to any other user ofthe social-networking system 160 with whom a user has formed aconnection, association, or relationship via the social-networkingsystem 160.

In particular embodiments, the social-networking system 160 may provideusers with the ability to take actions on various types of items orobjects, supported by the social-networking system 160. As an exampleand not by way of limitation, the items and objects may include groupsor social networks to which users of the social-networking system 160may belong, events or calendar entries in which a user might beinterested, computer-based applications that a user may use,transactions that allow users to buy or sell items via the service,interactions with advertisements that a user may perform, or othersuitable items or objects. A user may interact with anything that iscapable of being represented in the social-networking system 160 or byan external system of a third-party system 170, which is separate fromthe social-networking system 160 and coupled to the social-networkingsystem 160 via a network 110.

In particular embodiments, the social-networking system 160 may becapable of linking a variety of entities. As an example and not by wayof limitation, the social-networking system 160 may enable users tointeract with each other as well as receive content from third-partysystems 170 or other entities, or to allow users to interact with theseentities through an application programming interfaces (API) or othercommunication channels.

In particular embodiments, a third-party system 170 may include one ormore types of servers, one or more data stores, one or more interfaces,including but not limited to APIs, one or more web services, one or morecontent sources, one or more networks, or any other suitable components,e.g., that servers may communicate with. A third-party system 170 may beoperated by a different entity from an entity operating thesocial-networking system 160. In particular embodiments, however, thesocial-networking system 160 and third-party systems 170 may operate inconjunction with each other to provide social-networking services tousers of the social-networking system 160 or third-party systems 170. Inthis sense, the social-networking system 160 may provide a platform, orbackbone, which other systems, such as third-party systems 170, may useto provide social-networking services and functionality to users acrossthe Internet.

In particular embodiments, a third-party system 170 may include athird-party content object provider. A third-party content objectprovider may include one or more sources of content objects, which maybe communicated to a client system 130. As an example and not by way oflimitation, content objects may include information regarding things oractivities of interest to the user, such as, for example, movie showtimes, movie reviews, restaurant reviews, restaurant menus, productinformation and reviews, or other suitable information. As anotherexample and not by way of limitation, content objects may includeincentive content objects, such as coupons, discount tickets, giftcertificates, or other suitable incentive objects.

In particular embodiments, the social-networking system 160 alsoincludes user-generated content objects, which may enhance a user'sinteractions with the social-networking system 160. User-generatedcontent may include anything a user can add, upload, send, or “post” tothe social-networking system 160. As an example and not by way oflimitation, a user communicates posts to the social-networking system160 from a client system 130. Posts may include data such as statusupdates or other textual data, location information, photos, videos,links, music or other similar data or media. Content may also be addedto the social-networking system 160 by a third-party through a“communication channel,” such as a newsfeed or stream.

In particular embodiments, the social-networking system 160 may includea variety of servers, sub-systems, programs, modules, logs, and datastores. In particular embodiments, the social-networking system 160 mayinclude one or more of the following: a web server, action logger,API-request server, relevance-and-ranking engine, content-objectclassifier, notification controller, action log,third-party-content-object-exposure log, inference module,authorization/privacy server, search module, advertisement-targetingmodule, user-interface module, user-profile store, connection store,third-party content store, or location store. The social-networkingsystem 160 may also include suitable components such as networkinterfaces, security mechanisms, load balancers, failover servers,management-and-network-operations consoles, other suitable components,or any suitable combination thereof. In particular embodiments, thesocial-networking system 160 may include one or more user-profile storesfor storing user profiles. A user profile may include, for example,biographic information, demographic information, behavioral information,social information, or other types of descriptive information, such aswork experience, educational history, hobbies or preferences, interests,affinities, or location. Interest information may include interestsrelated to one or more categories. Categories may be general orspecific. As an example and not by way of limitation, if a user “likes”an article about a brand of shoes the category may be the brand, or thegeneral category of “shoes” or “clothing.” A connection store may beused for storing connection information about users. The connectioninformation may indicate users who have similar or common workexperience, group memberships, hobbies, educational history, or are inany way related or share common attributes. The connection informationmay also include user-defined connections between different users andcontent (both internal and external). A web server may be used forlinking the social-networking system 160 to one or more client systems130 or one or more third-party systems 170 via a network 110. The webserver may include a mail server or other messaging functionality forreceiving and routing messages between the social-networking system 160and one or more client systems 130. An API-request server may allow athird-party system 170 to access information from the social-networkingsystem 160 by calling one or more APIs. An action logger may be used toreceive communications from a web server about a user's actions on oroff the social-networking system 160. In conjunction with the actionlog, a third-party-content-object log may be maintained of userexposures to third-party-content objects. A notification controller mayprovide information regarding content objects to a client system 130.Information may be pushed to a client system 130 as notifications, orinformation may be pulled from a client system 130 responsive to arequest received from a client system 130. Authorization servers may beused to enforce one or more privacy settings of the users of thesocial-networking system 160. A privacy setting of a user determines howparticular information associated with a user can be shared. Theauthorization server may allow users to opt in to or opt out of havingtheir actions logged by the social-networking system 160 or shared withother systems (e.g., a third-party system 170), such as, for example, bysetting appropriate privacy settings. Third-party-content-object storesmay be used to store content objects received from third parties, suchas a third-party system 170. Location stores may be used for storinglocation information received from client systems 130 associated withusers. Advertisement-pricing modules may combine social information, thecurrent time, location information, or other suitable information toprovide relevant advertisements, in the form of notifications, to auser.

Social Graphs

FIG. 2 illustrates an example social graph 200. In particularembodiments, the social-networking system 160 may store one or moresocial graphs 200 in one or more data stores. In particular embodiments,the social graph 200 may include multiple nodes—which may includemultiple user nodes 202 or multiple concept nodes 204—and multiple edges206 connecting the nodes. The example social graph 200 illustrated inFIG. 2 is shown, for didactic purposes, in a two-dimensional visual maprepresentation. In particular embodiments, a social-networking system160, a client system 130, or a third-party system 170 may access thesocial graph 200 and related social-graph information for suitableapplications. The nodes and edges of the social graph 200 may be storedas data objects, for example, in a data store (such as a social-graphdatabase). Such a data store may include one or more searchable orqueryable indexes of nodes or edges of the social graph 200.

In particular embodiments, a user node 202 may correspond to a user ofthe social-networking system 160. As an example and not by way oflimitation, a user may be an individual (human user), an entity (e.g.,an enterprise, business, or third-party application), or a group (e.g.,of individuals or entities) that interacts or communicates with or overthe social-networking system 160. In particular embodiments, when a userregisters for an account with the social-networking system 160, thesocial-networking system 160 may create a user node 202 corresponding tothe user, and store the user node 202 in one or more data stores. Usersand user nodes 202 described herein may, where appropriate, refer toregistered users and user nodes 202 associated with registered users. Inaddition or as an alternative, users and user nodes 202 described hereinmay, where appropriate, refer to users that have not registered with thesocial-networking system 160. In particular embodiments, a user node 202may be associated with information provided by a user or informationgathered by various systems, including the social-networking system 160.As an example and not by way of limitation, a user may provide his orher name, profile picture, contact information, birth date, sex, maritalstatus, family status, employment, education background, preferences,interests, or other demographic information. In particular embodiments,a user node 202 may be associated with one or more data objectscorresponding to information associated with a user. In particularembodiments, a user node 202 may correspond to one or more webinterfaces.

In particular embodiments, a concept node 204 may correspond to aconcept. As an example and not by way of limitation, a concept maycorrespond to a place (such as, for example, a movie theater,restaurant, landmark, or city); a website (such as, for example, awebsite associated with the social-networking system 160 or athird-party website associated with a web-application server); an entity(such as, for example, a person, business, group, sports team, orcelebrity); a resource (such as, for example, an audio file, video file,digital photo, text file, structured document, or application) which maybe located within the social-networking system 160 or on an externalserver, such as a web-application server; real or intellectual property(such as, for example, a sculpture, painting, movie, game, song, idea,photograph, or written work); a game; an activity; an idea or theory;another suitable concept; or two or more such concepts. A concept node204 may be associated with information of a concept provided by a useror information gathered by various systems, including thesocial-networking system 160. As an example and not by way oflimitation, information of a concept may include a name or a title; oneor more images (e.g., an image of the cover page of a book); a location(e.g., an address or a geographical location); a website (which may beassociated with a URL); contact information (e.g., a phone number or anemail address); other suitable concept information; or any suitablecombination of such information. In particular embodiments, a conceptnode 204 may be associated with one or more data objects correspondingto information associated with concept node 204. In particularembodiments, a concept node 204 may correspond to one or more webinterfaces.

In particular embodiments, a node in the social graph 200 may representor be represented by a web interface (which may be referred to as a“profile interface”). Profile interfaces may be hosted by or accessibleto the social-networking system 160. Profile interfaces may also behosted on third-party websites associated with a third-party server 170.As an example and not by way of limitation, a profile interfacecorresponding to a particular external web interface may be theparticular external web interface and the profile interface maycorrespond to a particular concept node 204. Profile interfaces may beviewable by all or a selected subset of other users. As an example andnot by way of limitation, a user node 202 may have a correspondinguser-profile interface in which the corresponding user may add content,make declarations, or otherwise express himself or herself. As anotherexample and not by way of limitation, a concept node 204 may have acorresponding concept-profile interface in which one or more users mayadd content, make declarations, or express themselves, particularly inrelation to the concept corresponding to concept node 204.

In particular embodiments, a concept node 204 may represent athird-party web interface or resource hosted by a third-party system170. The third-party web interface or resource may include, among otherelements, content, a selectable or other icon, or other inter-actableobject representing an action or activity. As an example and not by wayof limitation, a third-party web interface may include a selectable iconsuch as “like,” “check-in,” “eat,” “recommend,” or another suitableaction or activity. A user viewing the third-party web interface mayperform an action by selecting one of the icons (e.g., “check-in”),causing a client system 130 to send to the social-networking system 160a message indicating the user's action. In response to the message, thesocial-networking system 160 may create an edge (e.g., a check-in-typeedge) between a user node 202 corresponding to the user and a conceptnode 204 corresponding to the third-party web interface or resource andstore edge 206 in one or more data stores.

In particular embodiments, a pair of nodes in the social graph 200 maybe connected to each other by one or more edges 206. An edge 206connecting a pair of nodes may represent a relationship between the pairof nodes. In particular embodiments, an edge 206 may include orrepresent one or more data objects or attributes corresponding to therelationship between a pair of nodes. As an example and not by way oflimitation, a first user may indicate that a second user is a “friend”of the first user. In response to this indication, the social-networkingsystem 160 may send a “friend request” to the second user. If the seconduser confirms the “friend request,” the social-networking system 160 maycreate an edge 206 connecting the first user's user node 202 to thesecond user's user node 202 in the social graph 200 and store edge 206as social-graph information in one or more of data stores 164. In theexample of FIG. 2 , the social graph 200 includes an edge 206 indicatinga friend relation between user nodes 202 of user “A” and user “B” and anedge indicating a friend relation between user nodes 202 of user “C” anduser “B.” Although this disclosure describes or illustrates particularedges 206 with particular attributes connecting particular user nodes202, this disclosure contemplates any suitable edges 206 with anysuitable attributes connecting user nodes 202. As an example and not byway of limitation, an edge 206 may represent a friendship, familyrelationship, business or employment relationship, fan relationship(including, e.g., liking, etc.), follower relationship, visitorrelationship (including, e.g., accessing, viewing, checking-in, sharing,etc.), subscriber relationship, superior/subordinate relationship,reciprocal relationship, non-reciprocal relationship, another suitabletype of relationship, or two or more such relationships. Moreover,although this disclosure generally describes nodes as being connected,this disclosure also describes users or concepts as being connected.Herein, references to users or concepts being connected may, whereappropriate, refer to the nodes corresponding to those users or conceptsbeing connected in the social graph 200 by one or more edges 206.

In particular embodiments, an edge 206 between a user node 202 and aconcept node 204 may represent a particular action or activity performedby a user associated with user node 202 toward a concept associated witha concept node 204. As an example and not by way of limitation, asillustrated in FIG. 2 , a user may “like,” “attended,” “played,”“listened,” “cooked,” “worked at,” or “watched” a concept, each of whichmay correspond to a edge type or subtype. A concept-profile interfacecorresponding to a concept node 204 may include, for example, aselectable “check in” icon (such as, for example, a clickable “check in”icon) or a selectable “add to favorites” icon. Similarly, after a userclicks these icons, the social-networking system 160 may create a“favorite” edge or a “check in” edge in response to a user's actioncorresponding to a respective action. As another example and not by wayof limitation, a user (user “C”) may listen to a particular song (“SongName”) using a particular application (a third-party online musicapplication). In this case, the social-networking system 160 may createa “listened” edge 206 and a “used” edge (as illustrated in FIG. 2 )between user nodes 202 corresponding to the user and concept nodes 204corresponding to the song and application to indicate that the userlistened to the song and used the application. Moreover, thesocial-networking system 160 may create a “played” edge 206 (asillustrated in FIG. 2 ) between concept nodes 204 corresponding to thesong and the application to indicate that the particular song was playedby the particular application. In this case, “played” edge 206corresponds to an action performed by an external application (thethird-party online music application) on an external audio file (thesong “Song Name”). Although this disclosure describes particular edges206 with particular attributes connecting user nodes 202 and conceptnodes 204, this disclosure contemplates any suitable edges 206 with anysuitable attributes connecting user nodes 202 and concept nodes 204.Moreover, although this disclosure describes edges between a user node202 and a concept node 204 representing a single relationship, thisdisclosure contemplates edges between a user node 202 and a concept node204 representing one or more relationships. As an example and not by wayof limitation, an edge 206 may represent both that a user likes and hasused at a particular concept. Alternatively, another edge 206 mayrepresent each type of relationship (or multiples of a singlerelationship) between a user node 202 and a concept node 204 (asillustrated in FIG. 2 between user node 202 for user “E” and conceptnode 204 for “online music application”).

In particular embodiments, the social-networking system 160 may createan edge 206 between a user node 202 and a concept node 204 in the socialgraph 200. As an example and not by way of limitation, a user viewing aconcept-profile interface (such as, for example, by using a web browseror a special-purpose application hosted by the user's client system 130)may indicate that he or she likes the concept represented by the conceptnode 204 by clicking or selecting a “Like” icon, which may cause theuser's client system 130 to send to the social-networking system 160 amessage indicating the user's liking of the concept associated with theconcept-profile interface. In response to the message, thesocial-networking system 160 may create an edge 206 between user node202 associated with the user and concept node 204, as illustrated by“like” edge 206 between the user and concept node 204. In particularembodiments, the social-networking system 160 may store an edge 206 inone or more data stores. In particular embodiments, an edge 206 may beautomatically formed by the social-networking system 160 in response toa particular user action. As an example and not by way of limitation, ifa first user uploads a picture, watches a movie, or listens to a song,an edge 206 may be formed between user node 202 corresponding to thefirst user and concept nodes 204 corresponding to those concepts.Although this disclosure describes forming particular edges 206 inparticular manners, this disclosure contemplates forming any suitableedges 206 in any suitable manner.

Search Queries on Online Social Networks

In particular embodiments, a user may submit a query to thesocial-networking system 160 by, for example, selecting a query input orinputting text into query field. A user of an online social network maysearch for information relating to a specific subject matter (e.g.,users, concepts, external content or resource) by providing a shortphrase describing the subject matter, often referred to as a “searchquery,” to a search engine. The query may be an unstructured text queryand may comprise one or more text strings (which may include one or moren-grams). In general, a user may input any character string into a queryfield to search for content on the social-networking system 160 thatmatches the text query. The social-networking system 160 may then searcha data store 164 (or, in particular, a social-graph database) toidentify content matching the query. The search engine may conduct asearch based on the query phrase using various search algorithms andgenerate search results that identify resources or content (e.g.,user-profile interfaces, content-profile interfaces, or externalresources) that are most likely to be related to the search query. Toconduct a search, a user may input or send a search query to the searchengine. In response, the search engine may identify one or moreresources that are likely to be related to the search query, each ofwhich may individually be referred to as a “search result,” orcollectively be referred to as the “search results” corresponding to thesearch query. The identified content may include, for example,social-graph elements (i.e., user nodes 202, concept nodes 204, edges206), profile interfaces, external web interfaces, or any combinationthereof. The social-networking system 160 may then generate asearch-results interface with search results corresponding to theidentified content and send the search-results interface to the user.The search results may be presented to the user, often in the form of alist of links on the search-results interface, each link beingassociated with a different interface that contains some of theidentified resources or content. In particular embodiments, each link inthe search results may be in the form of a Uniform Resource Locator(URL) that specifies where the corresponding interface is located andthe mechanism for retrieving it. The social-networking system 160 maythen send the search-results interface to the web browser 132 on theuser's client system 130. The user may then click on the URL links orotherwise select the content from the search-results interface to accessthe content from the social-networking system 160 or from an externalsystem (such as, for example, a third-party system 170), as appropriate.The resources may be ranked and presented to the user according to theirrelative degrees of relevance to the search query. The search resultsmay also be ranked and presented to the user according to their relativedegree of relevance to the user. In other words, the search results maybe personalized for the querying user based on, for example,social-graph information, user information, search or browsing historyof the user, or other suitable information related to the user. Inparticular embodiments, ranking of the resources may be determined by aranking algorithm implemented by the search engine. As an example andnot by way of limitation, resources that are more relevant to the searchquery or to the user may be ranked higher than the resources that areless relevant to the search query or the user. In particularembodiments, the search engine may limit its search to resources andcontent on the online social network. However, in particularembodiments, the search engine may also search for resources or contentson other sources, such as a third-party system 170, the internet orWorld Wide Web, or other suitable sources. Although this disclosuredescribes querying the social-networking system 160 in a particularmanner, this disclosure contemplates querying the social-networkingsystem 160 in any suitable manner.

Typeahead Processes and Queries

In particular embodiments, one or more client-side and/or backend(server-side) processes may implement and utilize a “typeahead” featurethat may automatically attempt to match social-graph elements (e.g.,user nodes 202, concept nodes 204, or edges 206) to informationcurrently being entered by a user in an input form rendered inconjunction with a requested interface (such as, for example, auser-profile interface, a concept-profile interface, a search-resultsinterface, a user interface/view state of a native applicationassociated with the online social network, or another suitable interfaceof the online social network), which may be hosted by or accessible inthe social-networking system 160. In particular embodiments, as a useris entering text to make a declaration, the typeahead feature mayattempt to match the string of textual characters being entered in thedeclaration to strings of characters (e.g., names, descriptions)corresponding to users, concepts, or edges and their correspondingelements in the social graph 200. In particular embodiments, when amatch is found, the typeahead feature may automatically populate theform with a reference to the social-graph element (such as, for example,the node name/type, node ID, edge name/type, edge ID, or anothersuitable reference or identifier) of the existing social-graph element.In particular embodiments, as the user enters characters into a formbox, the typeahead process may read the string of entered textualcharacters. As each keystroke is made, the frontend-typeahead processmay send the entered character string as a request (or call) to thebackend-typeahead process executing within the social-networking system160. In particular embodiments, the typeahead process may use one ormore matching algorithms to attempt to identify matching social-graphelements. In particular embodiments, when a match or matches are found,the typeahead process may send a response to the user's client system130 that may include, for example, the names (name strings) ordescriptions of the matching social-graph elements as well as,potentially, other metadata associated with the matching social-graphelements. As an example and not by way of limitation, if a user entersthe characters “pok” into a query field, the typeahead process maydisplay a drop-down menu that displays names of matching existingprofile interfaces and respective user nodes 202 or concept nodes 204,such as a profile interface named or devoted to “poker” or “poke,” whichthe user can then click on or otherwise select thereby confirming thedesire to declare the matched user or concept name corresponding to theselected node.

More information on typeahead processes may be found in U.S. patentapplication Ser. No. 12/763162, filed 19 Apr. 2010, and U.S. patentapplication Ser. No. 13/556072, filed 23 Jul. 2012, which areincorporated by reference.

In particular embodiments, the typeahead processes described herein maybe applied to search queries entered by a user. As an example and not byway of limitation, as a user enters text characters into a query field,a typeahead process may attempt to identify one or more user nodes 202,concept nodes 204, or edges 206 that match the string of charactersentered into the query field as the user is entering the characters. Asthe typeahead process receives requests or calls including a string orn-gram from the text query, the typeahead process may perform or causeto be performed a search to identify existing social-graph elements(i.e., user nodes 202, concept nodes 204, edges 206) having respectivenames, types, categories, or other identifiers matching the enteredtext. The typeahead process may use one or more matching algorithms toattempt to identify matching nodes or edges. When a match or matches arefound, the typeahead process may send a response to the user's clientsystem 130 that may include, for example, the names (name strings) ofthe matching nodes as well as, potentially, other metadata associatedwith the matching nodes. The typeahead process may then display adrop-down menu that displays names of matching existing profileinterfaces and respective user nodes 202 or concept nodes 204, anddisplays names of matching edges 206 that may connect to the matchinguser nodes 202 or concept nodes 204, which the user can then click on orotherwise select thereby confirming the desire to search for the matcheduser or concept name corresponding to the selected node, or to searchfor users or concepts connected to the matched users or concepts by thematching edges. Alternatively, the typeahead process may simplyauto-populate the form with the name or other identifier of thetop-ranked match rather than display a drop-down menu. The user may thenconfirm the auto-populated declaration simply by keying “enter” on akeyboard or by clicking on the auto-populated declaration. Upon userconfirmation of the matching nodes and edges, the typeahead process maysend a request that informs the social-networking system 160 of theuser's confirmation of a query containing the matching social-graphelements. In response to the request sent, the social-networking system160 may automatically (or alternately based on an instruction in therequest) call or otherwise search a social-graph database for thematching social-graph elements, or for social-graph elements connectedto the matching social-graph elements as appropriate. Although thisdisclosure describes applying the typeahead processes to search queriesin a particular manner, this disclosure contemplates applying thetypeahead processes to search queries in any suitable manner.

In connection with search queries and search results, particularembodiments may utilize one or more systems, components, elements,functions, methods, operations, or steps disclosed in U.S. patentapplication Ser. No. 11/503093, filed 11 Aug. 2006, U.S. patentapplication Ser. No. 12/977027, filed 22 Dec. 2010, and U.S. patentapplication Ser. No. 12/978265, filed 23 Dec. 2010, which areincorporated by reference.

Structured Search Queries

In particular embodiments, in response to a text query received from afirst user (i.e., the querying user), the social-networking system 160may parse the text query and identify portions of the text query thatcorrespond to particular social-graph elements. However, in some cases aquery may include one or more terms that are ambiguous, where anambiguous term is a term that may possibly correspond to multiplesocial-graph elements. To parse the ambiguous term, thesocial-networking system 160 may access a social graph 200 and thenparse the text query to identify the social-graph elements thatcorresponded to ambiguous n-grams from the text query. Thesocial-networking system 160 may then generate a set of structuredqueries, where each structured query corresponds to one of the possiblematching social-graph elements. These structured queries may be based onstrings generated by a grammar model, such that they are rendered in anatural-language syntax with references to the relevant social-graphelements. As an example and not by way of limitation, in response to thetext query, “show me friends of my girlfriend,” the social-networkingsystem 160 may generate a structured query “Friends of Stephanie,” where“Friends” and “Stephanie” in the structured query are referencescorresponding to particular social-graph elements. The reference to“Stephanie” would correspond to a particular user node 202 (where thesocial-networking system 160 has parsed the n-gram “my girlfriend” tocorrespond with a user node 202 for the user “Stephanie”), while thereference to “Friends” would correspond to friend-type edges 206connecting that user node 202 to other user nodes 202 (i.e., edges 206connecting to “Stephanie's” first-degree friends). When executing thisstructured query, the social-networking system 160 may identify one ormore user nodes 202 connected by friend-type edges 206 to the user node202 corresponding to “Stephanie”. As another example and not by way oflimitation, in response to the text query, “friends who work atfacebook,” the social-networking system 160 may generate a structuredquery “My friends who work at Facebook,” where “my friends,” “work at,”and “Facebook” in the structured query are references corresponding toparticular social-graph elements as described previously (i.e., afriend-type edge 206, a work-at-type edge 206, and concept node 204corresponding to the company “Facebook”). By providing suggestedstructured queries in response to a user's text query, thesocial-networking system 160 may provide a powerful way for users of theonline social network to search for elements represented in the socialgraph 200 based on their social-graph attributes and their relation tovarious social-graph elements. Structured queries may allow a queryinguser to search for content that is connected to particular users orconcepts in the social graph 200 by particular edge-types. Thestructured queries may be sent to the first user and displayed in adrop-down menu (via, for example, a client-side typeahead process),where the first user can then select an appropriate query to search forthe desired content. Some of the advantages of using the structuredqueries described herein include finding users of the online socialnetwork based upon limited information, bringing together virtualindexes of content from the online social network based on the relationof that content to various social-graph elements, or finding contentrelated to you and/or your friends. Although this disclosure describesgenerating particular structured queries in a particular manner, thisdisclosure contemplates generating any suitable structured queries inany suitable manner.

More information on element detection and parsing queries may be foundin U.S. patent application Ser. No. 13/556072, filed 23 Jul. 2012, U.S.patent application Ser. No. 13/731866, filed 31 Dec. 2012, and U.S.patent application Ser. No. 13/732101, filed 31 Dec. 2012, each of whichis incorporated by reference. More information on structured searchqueries and grammar models may be found in U.S. patent application Ser.No. 13/556072, filed 23 Jul. 2012, U.S. patent application Ser. No.13/674695, filed 12 Nov. 2012, and U.S. patent application Ser. No.13/731866, filed 31 Dec. 2012, each of which is incorporated byreference.

Generating Keywords and Keyword Queries

In particular embodiments, the social-networking system 160 may providecustomized keyword completion suggestions to a querying user as the useris inputting a text string into a query field. Keyword completionsuggestions may be provided to the user in a non-structured format. Inorder to generate a keyword completion suggestion, the social-networkingsystem 160 may access multiple sources within the social-networkingsystem 160 to generate keyword completion suggestions, score the keywordcompletion suggestions from the multiple sources, and then return thekeyword completion suggestions to the user. As an example and not by wayof limitation, if a user types the query “friends stan,” then thesocial-networking system 160 may suggest, for example, “friendsstanschool,” “friends stanschool university,” “friends stanley,”“friends stanley cooper,” “friends stanley kubrick,” “friends stanleycup,” and “friends stanlonski.” In this example, the social-networkingsystem 160 is suggesting the keywords which are modifications of theambiguous n-gram “stan,” where the suggestions may be generated from avariety of keyword generators. The social-networking system 160 may haveselected the keyword completion suggestions because the user isconnected in some way to the suggestions. As an example and not by wayof limitation, the querying user may be connected within the socialgraph 200 to the concept node 204 corresponding to Stanford University,for example by like- or attended-type edges 206. The querying user mayalso have a friend named Stanley Cooper. Although this disclosuredescribes generating keyword completion suggestions in a particularmanner, this disclosure contemplates generating keyword completionsuggestions in any suitable manner.

More information on keyword queries may be found in U.S. patentapplication Ser. No. 14/244748, filed 3 Apr. 2014, U.S. patentapplication Ser. No. 14/470607, filed 27 Aug. 2014, and U.S. patentapplication Ser. No. 14/561418, filed 5 Dec. 2014, each of which isincorporated by reference.

Recommendations From Post Comments

In particular embodiments, a user of an online social network may createa post on the online social network requesting recommendations for, byway of example, locations, activities, or services. As an example andnot by way of limitation, a user may post to the online social networkasking others for thing-to-do in a city, e.g., “I'm going to Barcelonanext week, what should I do there?” The user's friends on the onlinesocial network may then respond with suggestions in the post's commentssection. However, these recommendations from the user's friends on theonline social network may be provided in an unstructured way, and mayrequire the querying user to perform numerous subsequent queries on eachrecommendation to get more information. Thus, it would be useful if theonline social network could provide a structured, easy-to-use interfacefor a user to review and explore recommendations provided in response toa query in their posts.

In particular embodiments, the social-networking system 160 may generatea list of recommendations for a querying user based on a post by thequerying user and associated comments by other users. A user ofsocial-networking system 160 may create a post on the online socialnetwork requesting recommendations regarding, for example, a place, anactivity, a service, an event, etc. The social-networking system 160 mayparse user posts to detect when the post is asking for a recommendation,and convert the post into a recommendation list. The social-networkingsystem 160 may then parse comments submitted in response to the post todetect particular recommendations, and may identify objects that areassociated with the recommendation to form part of the list. As anexample and not by way of limitation, a user may create a post to theonline social network asking others for things-to-do in a city, e.g.,“I'm going to Barcelona next week, what should I do there?” The user'sfriends on the online social network may respond with suggestions in thepost's comments section, and the social-networking system 160 may parsethe comments to generate a recommendation list for “Things To Do inBarcelona.” The recommendation list may be displayed with complementaryinformation and functionality related to the identified recommendedobjects, such as ratings, reviews, a map displaying locations of theobjects, etc. Although this disclosure describes generating particularlists of recommendations in a particular manner, this disclosurecontemplates generating any suitable lists of recommendations in anysuitable manner.

In particular embodiments, the social-networking system 160 may receive,from a client system of a first user of an online social network, a textpost inputted by the first user. The user may enter the text post usinga composer interface of a webpage or application associated with theonline social network, or in any other manner suitable forsocial-networking system 160. As an example and not by way oflimitation, FIG. 3A illustrates a user typed and submitted a text postreading “Heading to Martha's Vineyard next weekend! What should I dowhile I'm there?” Although this disclosure describes receivingparticular posts from users in a particular manner, this disclosurecontemplates receiving any suitable posts from users in any suitablemanner.

In particular embodiments, the social-networking system 160 may detectthat a user is located in a particular geographic location and promptthe user to ask for recommendations related to the geographic location.As an example, FIG. 4A illustrates a scenario where a user has loggedinto the social-networking system 160 from Montreal. In response, thesocial-networking system 160 may provide a suggestion 404 that the userask friends on the online social network for travel recommendations(“Ask your friends for travel recommendations”), and an option for theuser to identify the post as a request for recommendations. Thesocial-networking system 160 may then format the text post to indicateto other users that the posting user is looking for recommendations, asillustrated by the text post 406. Although this disclosure describesprompting users to ask for recommendations in a particular manner, thisdisclosure contemplates prompting users to ask for recommendations inany suitable manner.

In particular embodiments, the social-networking system 160 may parsethe text of the post to identify a query associated with the post. Theparsing of the text of the post may be performed using any suitablemethods or systems, such as, for example, using a natural-languageparser, machine-learning classifying techniques, a probabilisticlanguage model, an n-gram model, a segmental Markov model, agrammar-language model, other suitable parsing methods or systems, orany combination thereof. As an example and not by way of limitation, thesocial-networking system 160 may use a natural-language parser toanalyze the text of the post reading “Heading to Martha's Vineyard nextweekend! What should I do while I'm there?” Based on the presence of thequestion mark in the text of the post and the interrogative “what”, thenatural-language parser may identify the post as being associated with aquery requesting recommendations from others. In connection with parsingtext to identify a query, particular embodiments may utilize one or moresystems, components, elements, functions, methods, operations, or stepsdisclosed in U.S. patent application Ser. No. 14/455798, filed 8 Aug.2014 and U.S. patent application Ser. No. 15/002226, filed 20 Jan. 2016,each of which is incorporated by reference. Although this disclosuredescribes parsing text in a particular manner, this disclosurecontemplates parsing text in any suitable any suitable manner.

In particular embodiments, the social-networking system 160 maycalculate a degree of confidence that the text post is associated withthe query. Based on an analysis of the text, the parser may determine alikelihood or probability of what specifically the user is requesting(e.g., object-type, specific objects referenced in the query). Then,when the degree of confidence is above a threshold, thesocial-networking system 160 may identify the particular query. Inparticular embodiments, the analysis also takes into account otherinformation in addition to the text, such as, for example, a socialcontext of the post, or the text of comments responsive to the post. Asan example and not by way of limitation, if the post is associated withthe user Checking-in to Montreal, the social-networking system 160 mayincrease its confidence that the user is asking for recommendationsabout Montreal. The calculated degree of confidence may be, for example,a confidence score, a probability, a quality, a ranking, anothersuitable type of score, or any combination thereof. As an example andnot by way of limitation, the social-Active networking system 160 maydetermine a probability score (also referred to simply as a“probability”) that the text post corresponds to a query. Theprobability score may indicate the level of similarity or relevancebetween the text post and particular query grammar structures. There maybe many different ways to calculate the probability. The presentdisclosure contemplates any suitable method to calculate a probabilityscore for query identified in a text post. In particular embodiments,the social-networking system 20 may determine a probability, p, thattext post is associated with a particular query. The probability, p, maybe calculated as the probability of corresponding to a particular query,q, given a particular text post, X. In other words, the probability maybe calculated as p=(q|X). As an example and not by way of limitation, aprobability that a text post is associated with a particular query maycalculated as an probability score denoted as p_(i,j,q). The input maybe a text post X=(x₁, x₂, . . . , x_(N)), and a set of classes. For each(i:j) and a class q, the social-networking system 160 may computep_(i,j,q)=p(class(x_(i:j))=q|X). In particular embodiments, if thedegree of confidence is above the threshold, the social-networkingsystem 160 may then transform the post into a recommendation list typeof post. The social-networking system 160 may transform the post into arecommendation list automatically, or alternatively only after promptingthe user for a confirmation or approval to transform the post into arecommendation list (e.g., “Do you want to create a list of things-to-doin Barcelona, Spain?” In particular embodiments, the social-networkingsystem 160 may send a confirmation prompt for the first user to verifythe identified query. As an example and not by way of limitation, if thedegree of confidence is less than or equal to a particular thresholdconfidence, the social-networking system 160 may prompt the user, askingthe user to confirm if it is requesting something in particular (e.g.,“Are you asking for recommendations of things-to-do in Barcelona,Spain?”). In particular embodiments, the social-networking system mayuse a reaction-card type functionality, as disclosed in U.S. patentapplication Ser. No. 14/466269, filed 22 Aug. 2014, and which isincorporated by reference. Although this disclosure describesdetermining what specifically a user is requesting in a particularmanner, this disclosure contemplates determining what specifically auser is requesting in any suitable manner.

In particular embodiments, the parser may also use comments associatedwith the post as part of its analysis of the text to confirm thedetermination that the post is a request for recommendations. As anexample and not by way of limitation, to determine if the text post “I'mgoing to Barcelona next week, what should I do there?” is a query, thesocial-networking system 160 may analyze comments on the post todetermine if they are related to geographic locations in Barcelona, andif so the parser may increase its confidence that the original post wasa request for recommended locations in Barcelona. Although thisdisclosure describes confirming a determination that a post is a requestfor recommendations in a particular manner, this disclosure contemplatesconfirming a determination that a post is a request for recommendationsin any suitable manner.

In particular embodiments, the user may explicitly signal that a post isasking for recommendations, for example, through a user interfaceelement. The text post inputted by the first user may comprise one ormore characters inputted into, for example, a composer interface. As theuser types the characters, a typeahead process may parse and identifypotential queries for generating recommendation lists. In particularembodiments, the social-networking system 160 may read, by afrontend-typeahead process, the one or more characters as they areinputted into the compose interface and identify, by a backend-typeaheadprocess, one or more potential queries based on the one or morecharacters. The social-networking system 160 may then send, to theclient system 130, a prompt listing one or more of the potential queriesto the first user for selection. As an example and not by way oflimitation, in response to the user inputting “I'm going to Barcelonanext week, what . . . ” into a composer interface, the social-networkingsystem 160 may display a few suggested queries as the user types theinput, such as a typeahead-like suggestion of “Ask Friends forThings-to-do for Barcelona, Spain” in a drop-down menu adjacent to thecomposer interface, and allow the user to click on one of thesuggestions to generate the post. Although this disclosure describes auser signaling that a post is asking for recommendations in a particularmanner, this disclosure contemplates a user signaling that a post is arequest for recommendations in any suitable manner.

In particular embodiments, the social-networking system 160 may receiveone or more comments responsive to the text post from one or more secondusers of the online social network. As an example and not by way oflimitation, with reference to FIG. 3B, in response to the user posting“Heading to Martha's Vineyard next weekend! What should I do while I'mthere?”, the posting user's friends on the online social network maypost comments 308 in response to the text post, for example, “Go toSlice of Life! Get the apple pie!” Although this disclosure describesreceiving comments in a particular manner, this disclosure contemplatesreceiving comments in any suitable manner.

In particular embodiments, the social-networking system 160 maydetermine, for each of the one or more received comments, whether thecomment includes a recommendation responsive to the query associatedwith the post. The analysis of the recommendations may be performedusing any suitable methods or systems, such as, for example, using anatural-language parser, machine-learning classifying techniques, aprobabilistic language model, an n-gram model, a segmental Markov model,a grammar-language model, other suitable parsing methods or systems, orany combination thereof. As an example and not by way of limitation, thesocial-networking system 160 may use a natural-language parser toanalyze the text of the comment “Go to Slice of Life! Get the applepie!” Based on the reference to a particular location “Slice of Life”and the reference to a particular product “apple pie”, thenatural-language parser may identify the comment as including arecommendation response to the query in the text post “Heading toMartha's Vineyard next weekend! What should I do while I'm there?”Although this disclosure describes determining whether a commentincludes a recommendation in a particular manner, this disclosurecontemplates determining whether a comment includes a recommendation inany suitable manner.

In particular embodiments, the social-networking system 160 mayidentify, for each comment with a responsive recommendation, one or moreobjects of the online social network associated with the recommendation.As other users add comments, the natural-language parser analyzes thecomments to identify what specifically the users are recommending (e.g.,specific objects referenced in the comment). The parser may determinethat the commenter is recommending a particular place, activity,service, event, etc. (e.g., Parc Guell in Barcelona, Spain) and a degreeof confidence that the determination is correct. Then, when the degreeof confidence is above a threshold, the social-networking system 160 mayidentify the particular object. The degree of confidence may be, forexample, a confidence score, a probability, a quality, a ranking,another suitable type of score, or any combination thereof. As anexample and not by way of limitation, the social-networking system 160may determine a probability score that the n-gram in a commentcorresponds to a social-graph element, such as a user node 302, aconcept node 304, or an edge 306 of social graph 300. The probabilityscore may indicate the level of similarity or relevance between then-gram and a particular social-graph element. There may be manydifferent ways to calculate the probability. The present disclosurecontemplates any suitable method to calculate a probability score for ann-gram identified in a search query. In particular embodiments, thesocial-networking system 160 may determine a probability, p, that ann-gram corresponds to a particular social-graph element. Theprobability, p, may be calculated as the probability of corresponding toa particular social-graph element, k, given a particular search query,X. In other words, the probability may be calculated as p=(k|X). As anexample and not by way of limitation, a probability that an n-gramcorresponds to a social-graph element may calculated as an probabilityscore denoted as p_(i,j,k). The input may be a text query X=(x₁, x₂, . .. , x_(N)), and a set of classes. For each (i:j) and a class k, thesocial-networking system 160 may computep_(i,j,k)=p(class(x_(i:j))=k|X). In particular embodiments, thesocial-networking system 160 may identify the objects using methods andtechniques for detecting social graph elements for structured searchqueries, as described in U.S. patent application Ser. No. 13/556072,filed 23 Jul. 2012, which is incorporated by reference. Although thisdisclosure describes identifying objects of the online social networkassociated with a recommendation in a particular manner, this disclosurecontemplates identifying objects of the online social network associatedwith a recommendation in any suitable manner.

In particular embodiments, a commenting user may specify a specificonline social network object that is being recommended. The one or morecomments from the one or more second users may comprise one or morecharacters inputted into, for example, a composer interface. Asillustrated in FIG. 5A, as the commenting user types characters 502, atypeahead process may parse and identify potential objects 504 forrecommendation. In particular embodiments, the social-networking system160 may read, by a frontend-typeahead process, the one or morecharacters as they are inputted into the compose interface and mayidentify, by a backend-typeahead process, one or more potential objectsbased on the one or more characters. The social-networking system 160may then send, to the commenting user, a prompt listing one or more ofthe potential objects for selection. As an example any not by way oflimitation, in response to the user inputting the comment “Go to theMontreal Biodome!” into a composer interface, the social-networkingsystem 160 may display a suggest entities as the user types the input,such as a typeahead-like suggestion of “Montreal Biodome Museum,Montreal, Canada” inline in the composer interface. In particularembodiments, the potential objects may be identified based on theirresponsiveness to the identified recommendation query. The commentinguser may select one of the potential objects to include a reference 506to the object in the comment, as shown in FIG. 5B. Although thisdisclosure describes a commenting user recommending particular objectsin a particular manner, this disclosure contemplates commenting usersrecommending any suitable objects in any suitable manner.

In particular embodiments, the posting user and/or the commenters may beable to confirm that the identified recommendations are correct. As anexample and not by way of limitation, in response to a user inputtingthe comment “You should visit Parc Guell. It's lovely!,” thesocial-networking system 160 may prompt a user to confirm that theidentified object is being recommended in the comment, for example, byproviding the user with the prompt “Would you like to recommend ParcGuell, Barcelona, Spain?” The user could then click on a confirmationelement in the prompt to confirm that the recommendation is for “ParcGuell, Barcelona, Spain.” Although this disclosure describes a postinguser and/or commenters confirming that an identified recommendation iscorrect in a particular manner, this disclosure contemplates a postinguser and/or commenters confirming that an identified recommendation iscorrect in any suitable manner.

In particular embodiments, when the social-networking system 160 doesnot automatically identify a recommendation, it may allow the user tomanually specify a recommendation. As an example and not by way oflimitation, in response to a user inputting the comment “You shouldcheck out the park with the Gaudi sculptures,” the natural-languageparser of the social-networking system 160 may fail to identify anobject associated with the comment (e.g., because no entity of socialgraph 200 matches “Gaudi sculptures”). In this case, thesocial-networking system 160 may allow a user to specify an object forrecommendation. As an example and not by way of limitation, thesocial-networking system 160 could provide the user with the prompt“Would you like to suggest a location in Barcelona?” along with atype-ahead process, as previously explained, to allow the user tospecify a location (e.g., in response to such a prompt, the user couldmanually input “parc guell” and the social-networking system 160 maysuggest an entity “Parc Guell, Barcelona”). Although this disclosuredescribes manually specifying particular recommendations in a particularmanner, this disclosure contemplates manually specifying any suitablerecommendations in any suitable manner.

In particular embodiments, the social-networking system 160 may generatean aggregated recommendation list responsive to the query associatedwith the post. The list may include references to one or more of theidentified objects referenced in the comments to the post. Theaggregated recommendation list may be sent to the posting user, to oneor more of the commenters, or to other users for display. In particularembodiments, the social-networking system 160 may generate a graphicalinterface for displaying the recommendation list. As an example and notby way of limitation, the recommendation list may be displayed in anuser interface of the online social network, such as, for example, anewsfeed or user profile page. Examples of graphical interfacesdisplaying the recommendation list are shown in FIGS. 6 and 7 . Inparticular embodiments, the graphical interface may further comprise amap displaying a location of one or more of the identified objects, animage associated with the identified query, additional content, such as,for example, a title or other text indicating that it is arecommendation list, other suitable content, or any combination thereof.As an example and not by way of limitation, FIG. 5B illustrates arecommendation list generated in response to the check-in post inMontreal, Quebec with the text “Just landed! What should I do?”, wherethe recommendation list shows an image of Montreal, and the text “A listby Erica Virtue and 1 other”, indicating that it is a recommendationlist. Although this disclosure describes displaying particularrecommendation lists in a particular manner, this disclosurecontemplates displaying any suitable recommendation lists in anysuitable manner.

In particular embodiments, the social-networking system 160 mayretrieve, for each identified object, content associated with theobject. The content may include one or more of a rating associated withthe object, an address associated with the object, a snippet associatedwith the object, a social context associated with the object, an imageassociated with the object, other suitable content associated with theobject, or any combination thereof. The retrieved content associatedwith the object may be included in the aggregated recommendation list.FIG. 6B illustrates an interface with listed recommendations 610including rating and complementary information associated with theidentified object (e.g., hours, cost, reservation information, etc.). Asan example and not by way of limitation, a recommendation for arestaurant called “Slice of Life” may include a rating (e.g., 4.8 out of5 stars), restaurant hours or an indication that it is currently “Open,”and whether reservations are required. A social context associated withthe object may indicate which of a user's friends on the online socialnetwork have “liked,” “checked-in,” or “recommended” the object. As anexample and not by way of limitation, a recommendation for The MontrealBiodome may include thumbnail profile pictures of a few friends in theonline social network that have previously “checked-in” at The MontrealBiodome, as shown in element 702 of FIG. 7A. Snippets may displayinformational highlights of an object on the online social network, suchas common words, phrases, or posts associated with the object. As anexample and not by way of limitation, a snippet may indicate that thatcomments or posts throughout the online social network about therestaurant “Slice of Life” frequently mention the “apple pie.” Moreinformation about snippets can be found in U.S. patent application Ser.No. 13/827214, filed 14 Mar. 2013, U.S. patent application Ser. No.14/797819 filed on 13 Jul. 2015, and U.S. patent application Ser. No.14/938685 filed 11 Nov. 2015, each of which is incorporated byreference. Although this disclosure describes retrieving particularcontent for identified objects in a particular manner, this disclosurecontemplates retrieving any suitable content for identified objects inany suitable manner.

In particular embodiments, the graphical interface may further displayone or more additional comments associated with one or more of theidentified objects. The comments associated with an identified objectmay be displayed adjacent to the corresponding reference to theidentified object. In particular embodiments, a graphical interface maydisplay the recommendations as a scrollable set of cards 702, asillustrated in FIG. 7A. A user may scroll horizontally to navigate thelist, which may contain complementary information or other contentassociated with the recommended objects. In particular embodiments, asshown in FIG. 7B, a user may scroll vertically to view commentsassociated with the particular recommendation. The additional commentsmay be comments responsive to a comment that recommended the particularobject. As an example and not by way of limitation, the interface maydisplay a card with the recommendation of “The Montreal Biodome,” andwhen a user scrolls down the interface may show the comment thatrecommended the Biodome (e.g., the comment by the user “Jill A Nussbaum”that says “Go to the Montreal Biodome!”) and additional comments relatedto the Biodome (e.g., “Don't miss the penguins!”). More informationabout cards can be found in U.S. patent application Ser. No. 14/258821,filed 22 Apr. 2014, which is incorporated by reference. Although thisdisclosure describes displaying particular recommendation lists in aparticular manner, this disclosure contemplates displaying any suitablerecommendation lists in any suitable manner.

In particular embodiments, users of social-networking system 160 mayview and interact with recommendation lists. The recommendation list maybe displayed in the newsfeeds of the posting user's friends or otherusers of the social-networking system 160. Users may interact with therecommendation lists by adding, removing, sharing the lists, taggingother users to the list, or sharing ownership of the list, among others.In particular embodiments, a recommendation list may contain the options606 illustrated in FIG. 6A that allow a user to “Like” the list, “Save”the list for later viewing, “Share” the list with other users of theonline social network, or “Edit” the list by adding or removingreferenced objects from the list. As an example and not by way oflimitation, a user may decide that there are too many restaurants in thelist, so the user may remove “The Black Dog Tavern” and add “SouthBeach.” In particular embodiments, the posting user may authorize one ormore other users as having viewing or editing rights to therecommendation list. As an example and not by way of limitation,referencing FIG. 6A, the user may access an access-control interfacethat allows the user to specify that the user's spouse and brother haveediting rights to the recommendation list “Things to Do in Martha'sVineyard,” and may further specify that the user's friends (i.e.,first-degree connections of the user in social graph 200) have viewingrights to the recommendation list. Although this disclosure describesinteracting with recommendation lists in a particular manner, thisdisclosure contemplates interacting with recommendation lists in anysuitable manner.

In particular embodiments, the social-networking system 160 may rank theone or more identified objects. The identified object in therecommendation list may be ranked based on one or more factors,including, for example, social-network information associated with theobjects, social signals (e.g., likes, check-ins, comments, posts,reshares, etc.) associated with the objects, ratings associated with theobjects, social-graph affinities of the querying user with respect tothe objects, other suitable factors, or any combination thereof. As anexample and not by way of limitation, the objects recommendation list of“Things to Do in Montreal” in of FIGS. 7A and 7B may be numbered indescending order of “likes” associated with each object (e.g., the most“liked” objects first, the second most “liked” objects second, and soon). Although this disclosure describes raking identified objects in aparticular manner, this disclosure contemplates ranking identifiedobjects in any suitable manner.

In particular embodiments, the social-networking system 160 may send anotification to the first user when the first user is within apredetermined distance of one or more of the identified objects. As anexample and not by way of limitation, referencing FIG. 6B, if one of therecommendations in a Martha's Vineyard list is the restaurant “Slice ofLife,” the social-networking system 160 may send a push notification(e.g., a text message saying “Slice of Life restaurant recommended byyour friend Emily Lancaster is nearby”) to the user's mobile device whenthe social-networking system 160 detects the user is located within 1mile (i.e., the predetermined distance) of the restaurant. In particularembodiments, online social network users may “like” or “follow” one ormore recommendation lists of other users, and the social-networkingsystem 160 may likewise send them notifications when they are within acertain distance of recommended objects. As an example and not by way oflimitation, the user's online social network friend Jill may press the“like” button associated with the Martha's Vineyard recommendation list,and at a later date receive a notification when the online socialnetwork detects she is within a predetermined distance of “The Black DogTavern” restaurant. Although this disclosure describes sendingnotifications in a particular manner, this disclosure contemplatessending notifications in any suitable manner.

In particular embodiments, the social-networking system 160 may maintainstatistics and conduct data analysis of recommendations lists throughoutthe network to improve the detection and recommendation system. Thesocial-networking system 160 may maintain data on how much each objectin the online social network is recommended, what social interactionsoccur with recommended objects, what are the particular preferences ofusers based on social context, or how user users interact withrecommendations lists, among others. As an example and not by way oflimitation, referencing FIG. 6B, in response to a user requestingrecommendations for Martha's Vineyard, the social-networking system 160may first determine that the user enjoys the outdoors and the beach,based on the user's prior photos, text posts, and other social context.The social-networking system 160 may then determine what are the mostrecommended outdoors places in Martha's Vineyard, and place them at thetop of the list (e.g., placing “South Beach,” “Aquinnah Cliffs,” and“Edgartown Lighthouse” at the top of the list.) Although this disclosuredescribes maintaining statistics and conducting data analysis in aparticular manner, this disclosure contemplates maintaining statisticsand conducting data analysis in any suitable manner.

In particular embodiments, the social-networking system 160 may detectthat a number of recommendations responsive to the query is below athreshold number of recommendations and may add one or more additionalrecommendations responsive to the query to the aggregated recommendationlist. When a user posts a recommendation request but receives few or nocomments, the social-networking system 160 may provide a list of defaultrecommendations obtained from various sources, such as search engines,prior lists, or other social-network data. As an example and not by wayof limitation, referencing FIG. 8 , if fewer than three (i.e., thethreshold number of recommendations) of the user's friends on the onlinesocial network have responded to the text post, the social-networkingsystem 160 may determine recommendations responsive to the query basedon social-network data. As illustrated in FIG. 8 , the social-networkingsystem 160 may add additional recommendations 802 to the aggregatedrecommendation list, which shows references to “Most Recommended”locations in Martha's Vineyard. Similarly, the additionalrecommendations 802 could include references to “Best Rated” locations,locations with “Most Check-ins”, etc. In particular embodiments, thesocial-networking system 160 may determine responsive recommendationsand may display them adjacent to the comments or other recommendationsin the list. As an example and not by way of limitation, the defaultrecommendations may be presented to the user immediately after the usersubmits the text post (e.g., in a reaction-card) so the user does nothave to wait for his friends on the online social network to commentwith their recommendations. Although this disclosure describespresenting default recommendations in a particular manner, thisdisclosure contemplates presenting default recommendations in anysuitable manner.

In particular embodiments, the query identified in a post may beassociated with a particular object of the online social network. As anexample and not by way of limitation, referencing FIG. 6B, thesocial-networking system 160 may analyze the post text “Heading toMartha's Vineyard next weekend!” and determine it is associated with aquery asking for recommendations for the island of Martha's Vineyard,which may be associated with a Martha's Vineyard entity object in thesocial-networking system 160 (which may be represented by a particularconcept node 204 in social graph 200). In particular embodiments, thesocial-networking system 160 may determine one or more second users thathave a social-graph affinity with respect to the particular objectassociated with the query that is above a predetermined thresholdaffinity, and then may send a notification to the one or more secondusers to provide an additional recommendation responsive to the query.As an example and not by way of limitation, if few or no users haveresponded with recommendations, the social-networking system 160 maysend notifications to other users that are associated with or haveinteracted with the Martha's Vineyard object in the past, prompting themto provide recommendations (e.g., “Your friend Stephanie is asking forrecommendations for Martha's Vineyard, leave a tip now!”). Although thisdisclosure describes prompting users to provide recommendations in aparticular manner, this disclosure contemplates prompting users toprovide recommendations in any suitable manner.

In particular embodiments, the social-networking system 160 may generatean itinerary referencing one or more of the identified objects based oninformation associated with the first user. The social-networking system160 may use complementary data associated with the identified object,for example, hours/days of service, distance, etc. to create aday-by-day or hour-by-hour itinerary that plans out the trip for theuser. As an example and not by way of limitation, the social-networkingsystem 160 may generate a recommendation list for Martha's Vineyard inresponse to a user post, and then may create a week long itinerary thatincludes the recommended objects (e.g., Friday at 6 pm arrive at“[brand-name] Hotel,” Friday at 8 pm dinner at “Slice of Life”restaurant, Saturday at 10 am arrive at “South Beach,” etc.). Inparticular embodiments, the social-networking system 160 mayautomatically create a travel itinerary based on the recommendations andother information obtained or inferred from social-network data, such asthe user's tastes, budget, etc. As an example and not by way oflimitation, social-network data or a social context associated with theuser may indicate that the user likes museums, golfing, and pizza. Thesocial-networking system 160 may then create a week long itinerary thatallocates a few days and times to certain museums, a few days and timesfor golfing at a particular golf club, and a lunch or dinner at aparticular pizza restaurant. Additionally, the online social network mayuse the lists to enable tasks such booking flights, hotels, entrancetickets, ride share or cab rides, reserving tables at restaurants, etc.Although this disclosure describes generating a travel itinerary in aparticular manner, this disclosure contemplates generating the itineraryin any suitable manner.

In particular embodiments, the social-networking system 160 may includereferences to sponsored objects as part of a recommendation list. Inthis manner, the social-networking system 160 may use the recommendationlists as a means of selling and providing advertising. As an example andnot by way of limitation, the “Slice of Life” restaurant in Martha'sVineyard may pay the social-networking system 160 to have its onlinesocial network object featured prominently on recommendation lists. As aresult, the social-networking system 160 may rank the “Slice of Life”restaurant higher and place it before other objects on a recommendationlist for Martha's Vineyard. Although this disclosure describes providingsponsored recommendations in a particular manner, this disclosurecontemplates providing sponsored recommendations in any suitable manner.

FIG. 9 illustrates an example method 900 for generating a list ofrecommendations based on an online social network post and associatedcomments. The method may begin at step 910, where the social-networkingsystem 160 may receive, from a client system of a first user of anonline social network, a text post inputted by the first user. At step920, the social-networking system 160 may parse the text post toidentify a query associated with the post. At step 930, thesocial-networking system 160 may receive one or more comments responsiveto the text post from one or more second users of the online socialnetwork. At step 940, the social-networking system 160 may determine,for each of the one or more received comments, whether the commentincludes a recommendation responsive to the query associated with thepost. At step 950, the social-networking system 160 may identify, foreach comment with a responsive recommendation, one or more objects ofthe online social network associated with the recommendation. At step960, the social-networking system 160 may generate an aggregatedrecommendation list responsive to the query associated with the post,wherein the list includes references to one or more of the identifiedobjects. Particular embodiments may repeat one or more steps of themethod of FIG. 9 , where appropriate. Although this disclosure describesand illustrates particular steps of the method of FIG. 9 as occurring ina particular order, this disclosure contemplates any suitable steps ofthe method of FIG. 9 occurring in any suitable order. Moreover, althoughthis disclosure describes and illustrates an example method forgenerating a list of recommendations based on an online social networkpost and associated comments including the particular steps of themethod of FIG. 9 , this disclosure contemplates any suitable method forgenerating a list of recommendations based on an online social networkpost and associated comments including any suitable steps, which mayinclude all, some, or none of the steps of the method of FIG. 9 , whereappropriate. Furthermore, although this disclosure describes andillustrates particular components, devices, or systems carrying outparticular steps of the method of FIG. 9 , this disclosure contemplatesany suitable combination of any suitable components, devices, or systemscarrying out any suitable steps of the method of FIG. 9 .

Social Graph Affinity and Coefficient

In particular embodiments, the social-networking system 160 maydetermine the social-graph affinity (which may be referred to herein as“affinity”) of various social-graph entities for each other. Affinitymay represent the strength of a relationship or level of interestbetween particular objects associated with the online social network,such as users, concepts, content, actions, advertisements, other objectsassociated with the online social network, or any suitable combinationthereof. Affinity may also be determined with respect to objectsassociated with third-party systems 170 or other suitable systems. Anoverall affinity for a social-graph entity for each user, subjectmatter, or type of content may be established. The overall affinity maychange based on continued monitoring of the actions or relationshipsassociated with the social-graph entity. Although this disclosuredescribes determining particular affinities in a particular manner, thisdisclosure contemplates determining any suitable affinities in anysuitable manner.

In particular embodiments, the social-networking system 160 may measureor quantify social-graph affinity using an affinity coefficient (whichmay be referred to herein as “coefficient”). The coefficient mayrepresent or quantify the strength of a relationship between particularobjects associated with the online social network. The coefficient mayalso represent a probability or function that measures a predictedprobability that a user will perform a particular action based on theuser's interest in the action. In this way, a user's future actions maybe predicted based on the user's prior actions, where the coefficientmay be calculated at least in part on the history of the user's actions.Coefficients may be used to predict any number of actions, which may bewithin or outside of the online social network. As an example and not byway of limitation, these actions may include various types ofcommunications, such as sending messages, posting content, or commentingon content; various types of observation actions, such as accessing orviewing profile interfaces, media, or other suitable content; varioustypes of coincidence information about two or more social-graphentities, such as being in the same group, tagged in the samephotograph, checked-in at the same location, or attending the sameevent; or other suitable actions. Although this disclosure describesmeasuring affinity in a particular manner, this disclosure contemplatesmeasuring affinity in any suitable manner.

In particular embodiments, the social-networking system 160 may use avariety of factors to calculate a coefficient. These factors mayinclude, for example, user actions, types of relationships betweenobjects, location information, other suitable factors, or anycombination thereof. In particular embodiments, different factors may beweighted differently when calculating the coefficient. The weights foreach factor may be static or the weights may change according to, forexample, the user, the type of relationship, the type of action, theuser's location, and so forth. Ratings for the factors may be combinedaccording to their weights to determine an overall coefficient for theuser. As an example and not by way of limitation, particular useractions may be assigned both a rating and a weight while a relationshipassociated with the particular user action is assigned a rating and acorrelating weight (e.g., so the weights total 100%). To calculate thecoefficient of a user towards a particular object, the rating assignedto the user's actions may comprise, for example, 60% of the overallcoefficient, while the relationship between the user and the object maycomprise 40% of the overall coefficient. In particular embodiments, thesocial-networking system 160 may consider a variety of variables whendetermining weights for various factors used to calculate a coefficient,such as, for example, the time since information was accessed, decayfactors, frequency of access, relationship to information orrelationship to the object about which information was accessed,relationship to social-graph entities connected to the object, short- orlong-term averages of user actions, user feedback, other suitablevariables, or any combination thereof. As an example and not by way oflimitation, a coefficient may include a decay factor that causes thestrength of the signal provided by particular actions to decay withtime, such that more recent actions are more relevant when calculatingthe coefficient. The ratings and weights may be continuously updatedbased on continued tracking of the actions upon which the coefficient isbased. Any type of process or algorithm may be employed for assigning,combining, averaging, and so forth the ratings for each factor and theweights assigned to the factors. In particular embodiments, thesocial-networking system 160 may determine coefficients usingmachine-learning algorithms trained on historical actions and past userresponses, or data farmed from users by exposing them to various optionsand measuring responses. Although this disclosure describes calculatingcoefficients in a particular manner, this disclosure contemplatescalculating coefficients in any suitable manner.

In particular embodiments, the social-networking system 160 maycalculate a coefficient based on a user's actions. The social-networkingsystem 160 may monitor such actions on the online social network, on athird-party system 170, on other suitable systems, or any combinationthereof. Any suitable type of user actions may be tracked or monitored.Typical user actions include viewing profile interfaces, creating orposting content, interacting with content, tagging or being tagged inimages, joining groups, listing and confirming attendance at events,checking-in at locations, liking particular interfaces, creatinginterfaces, and performing other tasks that facilitate social action. Inparticular embodiments, the social-networking system 160 may calculate acoefficient based on the user's actions with particular types ofcontent. The content may be associated with the online social network, athird-party system 170, or another suitable system. The content mayinclude users, profile interfaces, posts, news stories, headlines,instant messages, chat room conversations, emails, advertisements,pictures, video, music, other suitable objects, or any combinationthereof. The social-networking system 160 may analyze a user's actionsto determine whether one or more of the actions indicate an affinity forsubject matter, content, other users, and so forth. As an example andnot by way of limitation, if a user may make frequently posts contentrelated to “coffee” or variants thereof, the social-networking system160 may determine the user has a high coefficient with respect to theconcept “coffee”. Particular actions or types of actions may be assigneda higher weight and/or rating than other actions, which may affect theoverall calculated coefficient. As an example and not by way oflimitation, if a first user emails a second user, the weight or therating for the action may be higher than if the first user simply viewsthe user-profile interface for the second user.

In particular embodiments, the social-networking system 160 maycalculate a coefficient based on the type of relationship betweenparticular objects. Referencing the social graph 200, thesocial-networking system 160 may analyze the number and/or type of edges206 connecting particular user nodes 202 and concept nodes 204 whencalculating a coefficient. As an example and not by way of limitation,user nodes 202 that are connected by a spouse-type edge (representingthat the two users are married) may be assigned a higher coefficientthan a user nodes 202 that are connected by a friend-type edge. In otherwords, depending upon the weights assigned to the actions andrelationships for the particular user, the overall affinity may bedetermined to be higher for content about the user's spouse than forcontent about the user's friend. In particular embodiments, therelationships a user has with another object may affect the weightsand/or the ratings of the user's actions with respect to calculating thecoefficient for that object. As an example and not by way of limitation,if a user is tagged in first photo, but merely likes a second photo, thesocial-networking system 160 may determine that the user has a highercoefficient with respect to the first photo than the second photobecause having a tagged-in-type relationship with content may beassigned a higher weight and/or rating than having a like-typerelationship with content. In particular embodiments, thesocial-networking system 160 may calculate a coefficient for a firstuser based on the relationship one or more second users have with aparticular object. In other words, the connections and coefficientsother users have with an object may affect the first user's coefficientfor the object. As an example and not by way of limitation, if a firstuser is connected to or has a high coefficient for one or more secondusers, and those second users are connected to or have a highcoefficient for a particular object, the social-networking system 160may determine that the first user should also have a relatively highcoefficient for the particular object. In particular embodiments, thecoefficient may be based on the degree of separation between particularobjects. The lower coefficient may represent the decreasing likelihoodthat the first user will share an interest in content objects of theuser that is indirectly connected to the first user in the social graph200. As an example and not by way of limitation, social-graph entitiesthat are closer in the social graph 200 (i.e., fewer degrees ofseparation) may have a higher coefficient than entities that are furtherapart in the social graph 200.

In particular embodiments, the social-networking system 160 maycalculate a coefficient based on location information. Objects that aregeographically closer to each other may be considered to be more relatedor of more interest to each other than more distant objects. Inparticular embodiments, the coefficient of a user towards a particularobject may be based on the proximity of the object's location to acurrent location associated with the user (or the location of a clientsystem 130 of the user). A first user may be more interested in otherusers or concepts that are closer to the first user. As an example andnot by way of limitation, if a user is one mile from an airport and twomiles from a gas station, the social-networking system 160 may determinethat the user has a higher coefficient for the airport than the gasstation based on the proximity of the airport to the user.

In particular embodiments, the social-networking system 160 may performparticular actions with respect to a user based on coefficientinformation. Coefficients may be used to predict whether a user willperform a particular action based on the user's interest in the action.A coefficient may be used when generating or presenting any type ofobjects to a user, such as advertisements, search results, news stories,media, messages, notifications, or other suitable objects. Thecoefficient may also be utilized to rank and order such objects, asappropriate. In this way, the social-networking system 160 may provideinformation that is relevant to user's interests and currentcircumstances, increasing the likelihood that they will find suchinformation of interest. In particular embodiments, thesocial-networking system 160 may generate content based on coefficientinformation. Content objects may be provided or selected based oncoefficients specific to a user. As an example and not by way oflimitation, the coefficient may be used to generate media for the user,where the user may be presented with media for which the user has a highoverall coefficient with respect to the media object. As another exampleand not by way of limitation, the coefficient may be used to generateadvertisements for the user, where the user may be presented withadvertisements for which the user has a high overall coefficient withrespect to the advertised object. In particular embodiments, thesocial-networking system 160 may generate search results based oncoefficient information. Search results for a particular user may bescored or ranked based on the coefficient associated with the searchresults with respect to the querying user. As an example and not by wayof limitation, search results corresponding to objects with highercoefficients may be ranked higher on a search-results interface thanresults corresponding to objects having lower coefficients.

In particular embodiments, the social-networking system 160 maycalculate a coefficient in response to a request for a coefficient froma particular system or process. To predict the likely actions a user maytake (or may be the subject of) in a given situation, any process mayrequest a calculated coefficient for a user. The request may alsoinclude a set of weights to use for various factors used to calculatethe coefficient. This request may come from a process running on theonline social network, from a third-party system 170 (e.g., via an APIor other communication channel), or from another suitable system. Inresponse to the request, the social-networking system 160 may calculatethe coefficient (or access the coefficient information if it haspreviously been calculated and stored). In particular embodiments, thesocial-networking system 160 may measure an affinity with respect to aparticular process. Different processes (both internal and external tothe online social network) may request a coefficient for a particularobject or set of objects. The social-networking system 160 may provide ameasure of affinity that is relevant to the particular process thatrequested the measure of affinity. In this way, each process receives ameasure of affinity that is tailored for the different context in whichthe process will use the measure of affinity.

In connection with social-graph affinity and affinity coefficients,particular embodiments may utilize one or more systems, components,elements, functions, methods, operations, or steps disclosed in U.S.patent application Ser. No. 11/503093, filed 11 Aug. 2006, U.S. patentapplication Ser. No. 12/977027, filed 22 Dec. 2010, U.S. patentapplication Ser. No. 12/978265, filed 23 Dec. 2010, and U.S. patentapplication Ser. No. 13/632869, filed 1 Oct. 2012, each of which isincorporated by reference.

Advertising

In particular embodiments, an advertisement may be text (which may beHTML-linked), one or more images (which may be HTML-linked), one or morevideos, audio, one or more ADOBE FLASH files, a suitable combination ofthese, or any other suitable advertisement in any suitable digitalformat presented on one or more web interfaces, in one or more e-mails,or in connection with search results requested by a user. In addition oras an alternative, an advertisement may be one or more sponsored stories(e.g., a news-feed or ticker item on the social-networking system 160).A sponsored story may be a social action by a user (such as “liking” aninterface, “liking” or commenting on a post on an interface, RSVPing toan event associated with an interface, voting on a question posted on aninterface, checking in to a place, using an application or playing agame, or “liking” or sharing a website) that an advertiser promotes, forexample, by having the social action presented within a pre-determinedarea of a profile interface of a user or other interface, presented withadditional information associated with the advertiser, bumped up orotherwise highlighted within news feeds or tickers of other users, orotherwise promoted. The advertiser may pay to have the social actionpromoted. As an example and not by way of limitation, advertisements maybe included among the search results of a search-results interface,where sponsored content is promoted over non-sponsored content.

In particular embodiments, an advertisement may be requested for displaywithin social-networking-system web interfaces, third-party webinterfaces, or other interfaces. An advertisement may be displayed in adedicated portion of an interface, such as in a banner area at the topof the interface, in a column at the side of the interface, in a GUIwithin the interface, in a pop-up window, in a drop-down menu, in aninput field of the interface, over the top of content of the interface,or elsewhere with respect to the interface. In addition or as analternative, an advertisement may be displayed within an application. Anadvertisement may be displayed within dedicated interfaces, requiringthe user to interact with or watch the advertisement before the user mayaccess an interface or utilize an application. The user may, for exampleview the advertisement through a web browser.

A user may interact with an advertisement in any suitable manner. Theuser may click or otherwise select the advertisement. By selecting theadvertisement, the user may be directed to (or a browser or otherapplication being used by the user) an interface associated with theadvertisement. At the interface associated with the advertisement, theuser may take additional actions, such as purchasing a product orservice associated with the advertisement, receiving informationassociated with the advertisement, or subscribing to a newsletterassociated with the advertisement. An advertisement with audio or videomay be played by selecting a component of the advertisement (like a“play button”). Alternatively, by selecting the advertisement, thesocial-networking system 160 may execute or modify a particular actionof the user.

An advertisement may also include social-networking-system functionalitythat a user may interact with. As an example and not by way oflimitation, an advertisement may enable a user to “like” or otherwiseendorse the advertisement by selecting an icon or link associated withendorsement. As another example and not by way of limitation, anadvertisement may enable a user to search (e.g., by executing a query)for content related to the advertiser. Similarly, a user may share theadvertisement with another user (e.g., through the social-networkingsystem 160) or RSVP (e.g., through the social-networking system 160) toan event associated with the advertisement. In addition or as analternative, an advertisement may include social-networking-systemcontent directed to the user. As an example and not by way oflimitation, an advertisement may display information about a friend ofthe user within the social-networking system 160 who has taken an actionassociated with the subject matter of the advertisement.

Systems and Methods

FIG. 10 illustrates an example computer system 1000. In particularembodiments, one or more computer systems 1000 perform one or more stepsof one or more methods described or illustrated herein. In particularembodiments, one or more computer systems 1000 provide functionalitydescribed or illustrated herein. In particular embodiments, softwarerunning on one or more computer systems 1000 performs one or more stepsof one or more methods described or illustrated herein or providesfunctionality described or illustrated herein. Particular embodimentsinclude one or more portions of one or more computer systems 1000.Herein, reference to a computer system may encompass a computing device,and vice versa, where appropriate. Moreover, reference to a computersystem may encompass one or more computer systems, where appropriate.

This disclosure contemplates any suitable number of computer systems1000. This disclosure contemplates computer system 1000 taking anysuitable physical form. As example and not by way of limitation,computer system 1000 may be an embedded computer system, asystem-on-chip (SOC), a single-board computer system (SBC) (such as, forexample, a computer-on-module (COM) or system-on-module (SOM)), adesktop computer system, a laptop or notebook computer system, aninteractive kiosk, a mainframe, a mesh of computer systems, a mobiletelephone, a personal digital assistant (PDA), a server, a tabletcomputer system, or a combination of two or more of these. Whereappropriate, computer system 1000 may include one or more computersystems 1000; be unitary or distributed; span multiple locations; spanmultiple machines; span multiple data centers; or reside in a cloud,which may include one or more cloud components in one or more networks.Where appropriate, one or more computer systems 1000 may perform withoutsubstantial spatial or temporal limitation one or more steps of one ormore methods described or illustrated herein. As an example and not byway of limitation, one or more computer systems 1000 may perform in realtime or in batch mode one or more steps of one or more methods describedor illustrated herein. One or more computer systems 1000 may perform atdifferent times or at different locations one or more steps of one ormore methods described or illustrated herein, where appropriate.

In particular embodiments, computer system 1000 includes a processor1002, memory 1004, storage 1006, an input/output (I/O) interface 1008, acommunication interface 1010, and a bus 1012. Although this disclosuredescribes and illustrates a particular computer system having aparticular number of particular components in a particular arrangement,this disclosure contemplates any suitable computer system having anysuitable number of any suitable components in any suitable arrangement.

In particular embodiments, processor 1002 includes hardware forexecuting instructions, such as those making up a computer program. Asan example and not by way of limitation, to execute instructions,processor 1002 may retrieve (or fetch) the instructions from an internalregister, an internal cache, memory 1004, or storage 1006; decode andexecute them; and then write one or more results to an internalregister, an internal cache, memory 1004, or storage 1006. In particularembodiments, processor 1002 may include one or more internal caches fordata, instructions, or addresses. This disclosure contemplates processor1002 including any suitable number of any suitable internal caches,where appropriate. As an example and not by way of limitation, processor1002 may include one or more instruction caches, one or more datacaches, and one or more translation lookaside buffers (TLBs).Instructions in the instruction caches may be copies of instructions inmemory 1004 or storage 1006, and the instruction caches may speed upretrieval of those instructions by processor 1002. Data in the datacaches may be copies of data in memory 1004 or storage 1006 forinstructions executing at processor 1002 to operate on; the results ofprevious instructions executed at processor 1002 for access bysubsequent instructions executing at processor 1002 or for writing tomemory 1004 or storage 1006; or other suitable data. The data caches mayspeed up read or write operations by processor 1002. The TLBs may speedup virtual-address translation for processor 1002. In particularembodiments, processor 1002 may include one or more internal registersfor data, instructions, or addresses. This disclosure contemplatesprocessor 1002 including any suitable number of any suitable internalregisters, where appropriate. Where appropriate, processor 1002 mayinclude one or more arithmetic logic units (ALUs); be a multi-coreprocessor; or include one or more processors 1002. Although thisdisclosure describes and illustrates a particular processor, thisdisclosure contemplates any suitable processor.

In particular embodiments, memory 1004 includes main memory for storinginstructions for processor 1002 to execute or data for processor 1002 tooperate on. As an example and not by way of limitation, computer system1000 may load instructions from storage 1006 or another source (such as,for example, another computer system 1000) to memory 1004. Processor1002 may then load the instructions from memory 1004 to an internalregister or internal cache. To execute the instructions, processor 1002may retrieve the instructions from the internal register or internalcache and decode them. During or after execution of the instructions,processor 1002 may write one or more results (which may be intermediateor final results) to the internal register or internal cache. Processor1002 may then write one or more of those results to memory 1004. Inparticular embodiments, processor 1002 executes only instructions in oneor more internal registers or internal caches or in memory 1004 (asopposed to storage 1006 or elsewhere) and operates only on data in oneor more internal registers or internal caches or in memory 1004 (asopposed to storage 1006 or elsewhere). One or more memory buses (whichmay each include an address bus and a data bus) may couple processor1002 to memory 1004. Bus 1012 may include one or more memory buses, asdescribed below. In particular embodiments, one or more memorymanagement units (MMUs) reside between processor 1002 and memory 1004and facilitate accesses to memory 1004 requested by processor 1002. Inparticular embodiments, memory 1004 includes random access memory (RAM).This RAM may be volatile memory, where appropriate Where appropriate,this RAM may be dynamic RAM (DRAM) or static RAM (SRAM). Moreover, whereappropriate, this RAM may be single-ported or multi-ported RAM. Thisdisclosure contemplates any suitable RAM. Memory 1004 may include one ormore memories 1004, where appropriate. Although this disclosuredescribes and illustrates particular memory, this disclosurecontemplates any suitable memory.

In particular embodiments, storage 1006 includes mass storage for dataor instructions. As an example and not by way of limitation, storage1006 may include a hard disk drive (HDD), a floppy disk drive, flashmemory, an optical disc, a magneto-optical disc, magnetic tape, or aUniversal Serial Bus (USB) drive or a combination of two or more ofthese. Storage 1006 may include removable or non-removable (or fixed)media, where appropriate. Storage 1006 may be internal or external tocomputer system 1000, where appropriate. In particular embodiments,storage 1006 is non-volatile, solid-state memory. In particularembodiments, storage 1006 includes read-only memory (ROM). Whereappropriate, this ROM may be mask-programmed ROM, programmable ROM(PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM),electrically alterable ROM (EAROM), or flash memory or a combination oftwo or more of these. This disclosure contemplates mass storage 1006taking any suitable physical form. Storage 1006 may include one or morestorage control units facilitating communication between processor 1002and storage 1006, where appropriate. Where appropriate, storage 1006 mayinclude one or more storages 1006. Although this disclosure describesand illustrates particular storage, this disclosure contemplates anysuitable storage.

In particular embodiments, I/O interface 1008 includes hardware,software, or both, providing one or more interfaces for communicationbetween computer system 1000 and one or more I/O devices. Computersystem 1000 may include one or more of these I/O devices, whereappropriate. One or more of these I/O devices may enable communicationbetween a person and computer system 1000. As an example and not by wayof limitation, an I/O device may include a keyboard, keypad, microphone,monitor, mouse, printer, scanner, speaker, still camera, stylus, tablet,touch screen, trackball, video camera, another suitable I/O device or acombination of two or more of these. An I/O device may include one ormore sensors. This disclosure contemplates any suitable I/O devices andany suitable I/O interfaces 1008 for them. Where appropriate, I/Ointerface 1008 may include one or more device or software driversenabling processor 1002 to drive one or more of these I/O devices. I/Ointerface 1008 may include one or more I/O interfaces 1008, whereappropriate. Although this disclosure describes and illustrates aparticular I/O interface, this disclosure contemplates any suitable I/Ointerface.

In particular embodiments, communication interface 1010 includeshardware, software, or both providing one or more interfaces forcommunication (such as, for example, packet-based communication) betweencomputer system 1000 and one or more other computer systems 1000 or oneor more networks. As an example and not by way of limitation,communication interface 1010 may include a network interface controller(NIC) or network adapter for communicating with an Ethernet or otherwire-based network or a wireless NIC (WNIC) or wireless adapter forcommunicating with a wireless network, such as a WI-FI network. Thisdisclosure contemplates any suitable network and any suitablecommunication interface 1010 for it. As an example and not by way oflimitation, computer system 1000 may communicate with an ad hoc network,a personal area network (PAN), a local area network (LAN), a wide areanetwork (WAN), a metropolitan area network (MAN), or one or moreportions of the Internet or a combination of two or more of these. Oneor more portions of one or more of these networks may be wired orwireless. As an example, computer system 1000 may communicate with awireless PAN (WPAN) (such as, for example, a BLUETOOTH WPAN), a WI-FInetwork, a WI-MAX network, a cellular telephone network (such as, forexample, a Global System for Mobile Communications (GSM) network), orother suitable wireless network or a combination of two or more ofthese. Computer system 1000 may include any suitable communicationinterface 1010 for any of these networks, where appropriate.Communication interface 1010 may include one or more communicationinterfaces 1010, where appropriate. Although this disclosure describesand illustrates a particular communication interface, this disclosurecontemplates any suitable communication interface.

In particular embodiments, bus 1012 includes hardware, software, or bothcoupling components of computer system 1000 to each other. As an exampleand not by way of limitation, bus 1012 may include an AcceleratedGraphics Port (AGP) or other graphics bus, an Enhanced Industry StandardArchitecture (EISA) bus, a front-side bus (FSB), a HYPERTRANSPORT (HT)interconnect, an Industry Standard Architecture (ISA) bus, an INFINIBANDinterconnect, a low-pin-count (LPC) bus, a memory bus, a Micro ChannelArchitecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, aPCI-Express (PCIe) bus, a serial advanced technology attachment (SATA)bus, a Video Electronics Standards Association local (VLB) bus, oranother suitable bus or a combination of two or more of these. Bus 1012may include one or more buses 1012, where appropriate. Although thisdisclosure describes and illustrates a particular bus, this disclosurecontemplates any suitable bus or interconnect.

Herein, a computer-readable non-transitory storage medium or media mayinclude one or more semiconductor-based or other integrated circuits(ICs) (such, as for example, field-programmable gate arrays (FPGAs) orapplication-specific ICs (ASICs)), hard disk drives (HDDs), hybrid harddrives (HHDs), optical discs, optical disc drives (ODDs),magneto-optical discs, magneto-optical drives, floppy diskettes, floppydisk drives (FDDs), magnetic tapes, solid-state drives (SSDs),RAM-drives, SECURE DIGITAL cards or drives, any other suitablecomputer-readable non-transitory storage media, or any suitablecombination of two or more of these, where appropriate. Acomputer-readable non-transitory storage medium may be volatile,non-volatile, or a combination of volatile and non-volatile, whereappropriate.

Miscellaneous

Herein, “or” is inclusive and not exclusive, unless expressly indicatedotherwise or indicated otherwise by context. Therefore, herein, “A or B”means “A, B, or both,” unless expressly indicated otherwise or indicatedotherwise by context. Moreover, “and” is both joint and several, unlessexpressly indicated otherwise or indicated otherwise by context.Therefore, herein, “A and B” means “A and B, jointly or severally,”unless expressly indicated otherwise or indicated otherwise by context.

The scope of this disclosure encompasses all changes, substitutions,variations, alterations, and modifications to the example embodimentsdescribed or illustrated herein that a person having ordinary skill inthe art would comprehend. The scope of this disclosure is not limited tothe example embodiments described or illustrated herein. Moreover,although this disclosure describes and illustrates respectiveembodiments herein as including particular components, elements,feature, functions, operations, or steps, any of these embodiments mayinclude any combination or permutation of any of the components,elements, features, functions, operations, or steps described orillustrated anywhere herein that a person having ordinary skill in theart would comprehend. Furthermore, reference in the appended claims toan apparatus or system or a component of an apparatus or system beingadapted to, arranged to, capable of, configured to, enabled to, operableto, or operative to perform a particular function encompasses thatapparatus, system, component, whether or not it or that particularfunction is activated, turned on, or unlocked, as long as thatapparatus, system, or component is so adapted, arranged, capable,configured, enabled, operable, or operative. Additionally, although thisdisclosure describes or illustrates particular embodiments as providingparticular advantages, particular embodiments may provide none, some, orall of these advantages.

What is claimed is:
 1. A method comprising, by one or more computingdevices: receiving, from a client system of a first user of an onlinesocial network, a text post inputted by the first user; parsing the textpost to identify a query associated with the text post; sending, to theclient system, instructions for presenting a confirmation promptrequesting confirmation of the identified query from the first user;receiving, from the client system, a confirmation of the identifiedquery from the first user; generating, in response to receiving theconfirmation, a recommendation list responsive to the query, wherein therecommendation list comprises references to one or more objectsreferenced in one or more prior comments associated with one or moreprior posts of the online social network associated with the query; andsending, to the client system, instructions for presenting therecommendation list to the first user.
 2. The method of claim 1, whereineach of the one or more prior comments referenced in the recommendationlist has a score based on social signals associated with the priorcomment.
 3. The method of claim 2, wherein the social signals compriseone or more of author information or location information associatedwith the prior comment.
 4. The method of claim 2, wherein each of theone or more prior comments referenced in the recommendation list has ascore greater than a threshold score.
 5. The method of claim 2, whereinthe one or more prior comments referenced in the recommendation list areranked based on their respective scores.
 6. The method of claim 1,wherein each of the one or more prior comments is responsive to thequery associated with the text post.
 7. The method of claim 1, whereinthe query is associated with one or more topics and one or morequery-domains that match the query.
 8. The method of claim 1, whereinthe recommendation list comprises an expandable thread user interfacefor at least one of the references to the one or more objects in therecommendation list.
 9. The method of claim 1, further comprisingsending, to one or more client systems of one or more second users,instructions for presenting the recommendation list to a second user ofthe one or more second users.
 10. The method of claim 1, wherein therecommendation list comprises, for each object referenced in therecommendation list, one or more of a rating associated with the object,an address associated with the object, a social context associated withthe object, or an image associated with the object.
 11. The method ofclaim 1, further comprising: sending, to the client system, instructionsfor presenting a user interface comprising the recommendation list,wherein the user interface further comprises a map displaying a locationof the one or more objects referenced in the recommendation list. 12.The method of claim 1, further comprising: sending, to the clientsystem, instructions for presenting a user interface comprising therecommendation list, wherein the user interface further comprises animage associated with the query.
 13. The method of claim 1, furthercomprising: sending, to the client system, instructions for presenting auser interface comprising the recommendation list, wherein the userinterface further comprises one or more additional comments associatedwith one or more objects referenced in comments adjacent to thecorresponding one or more references to the respective objects.
 14. Themethod of claim 1, wherein parsing the text post to identify the queryassociated with the text post comprises: calculating a degree ofconfidence that the text post is associated with the query; andidentifying the query when the degree of confidence is above athreshold.
 15. The method of claim 1, further comprising: receiving anindication when the client system is within a predetermined distance ofthe one or more objects referenced in the recommendation list; andsending, to the client system, a notification that the client system iswithin the predetermined distance of the one or more objects referencedin the recommendation list.
 16. The method of claim 1, furthercomprising: receiving, from the client system, a request for updates tothe recommendation list; generating updates to the recommendation list;and sending, to the client system, the updated recommendation list. 17.The method of claim 1, further comprising generating an itineraryreferencing the one or more objects based on an information associatedwith the first user.
 18. The method of claim 1, wherein the query isassociated with a particular object of the online social network, andwherein the method further comprises: determining one or more secondusers that have a social-graph affinity with respect to the particularobject above a predetermined threshold affinity; and sending anotification to the one or more second users to provide an additionalrecommendation responsive to the query.
 19. One or morecomputer-readable non-transitory storage media embodying software thatis operable when executed to: receive, from a client system of a firstuser of an online social network, a text post inputted by the firstuser; parse the text post to identify a query associated with the textpost; send, to the client system, instructions for presenting aconfirmation prompt requesting confirmation of the identified query fromthe first user; receive, from the client system, a confirmation of theidentified query from the first user; generate, in response to receivingthe confirmation, a recommendation list responsive to the query, whereinthe recommendation list comprises references to one or more objectsreferenced in one or more prior comments associated with one or moreprior posts of the online social network associated with the query; andsend, to the client system, instructions for presenting therecommendation list to the first user.
 20. A system comprising: one ormore processors; and a non-transitory memory coupled to the processorscomprising instructions executable by the processors, the processorsoperable when executing the instructions to: receive, from a clientsystem of a first user of an online social network, a text post inputtedby the first user; parse the text post to identify a query associatedwith the text post; send, to the client system, instructions forpresenting a confirmation prompt requesting confirmation of theidentified query from the first user; receive, from the client system, aconfirmation of the identified query from the first user; generate, inresponse to receiving the confirmation, a recommendation list responsiveto the query, wherein the recommendation list comprises references toone or more objects referenced in one or more prior comments associatedwith one or more prior posts of the online social network associatedwith the query; and send, to the client system, instructions forpresenting the recommendation list to the first user.